extractPCMBLOSUM {Rcpi} | R Documentation

## Generalized BLOSUM and PAM Matrix-Derived Descriptors

### Description

Generalized BLOSUM and PAM Matrix-Derived Descriptors

### Usage

    extractPCMBLOSUM(x, submat = "AABLOSUM62", k, lag, scale = TRUE,
      silent = TRUE)

### Arguments

`x` | A character vector, as the input protein sequence.
`submat` | Substitution matrix for the 20 amino acids. Should be one of `AABLOSUM45`, `AABLOSUM50`, `AABLOSUM62`, `AABLOSUM80`, `AABLOSUM100`, `AAPAM30`, `AAPAM40`, `AAPAM70`, `AAPAM120`, `AAPAM250`. Default is `'AABLOSUM62'`.
`k` | Integer. The number of selected scales (i.e. the first `k` scales) derived by the substitution matrix. This could be selected according to the printed relative importance values.
`lag` | The lag parameter. Must be less than the amino acids.
`scale` | Logical. Should we auto-scale the substitution matrix (`submat`) before doing eigen decomposition? Default is `TRUE`.
`silent` | Logical. Whether we print the relative importance of each scales (diagnal value of the eigen decomposition result matrix B) or not. Default is `TRUE`.

### Details

This function calculates the generalized BLOSUM matrix-derived descriptors. For users' convenience, `Rcpi` provides the BLOSUM45, BLOSUM50, BLOSUM62, BLOSUM80, BLOSUM100, PAM30, PAM40, PAM70, PAM120, and PAM250 matrices for the 20 amino acids to select.

### Value

A length `lag * p^2` named vector, `p` is the number of scales selected.

### Author(s)

Nan Xiao <https://nanx.me>

### References

Georgiev, A. G. (2009). Interpretable numerical descriptors of amino acid space. Journal of Computational Biology, 16(5), 703–723.

### Examples

    x = readFASTA(system.file('protseq/P00750.fasta', package = 'Rcpi'))[[1]]
    blosum = extractPCMBLOSUM(x, submat = 'AABLOSUM62', k = 5, lag = 7, scale = TRUE, silent = FALSE)

[Package Rcpi version 1.26.0 Index]